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Re-evaluating data management in the generative AI age

IBM Journey to AI blog

This requires traditional capabilities like encryption, anonymization and tokenization, but also creating capabilities to automatically classify data (sensitivity, taxonomy alignment) by using machine learning.

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Why data governance is essential for enterprise AI

IBM Journey to AI blog

If you add in IBM data governance solutions, the top left will look a bit more like this: The data governance solution powered by IBM Knowledge Catalog offers several capabilities to help facilitate advanced data discovery, automated data quality and data protection. and watsonx.data.

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Five benefits of a data catalog

IBM Journey to AI blog

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

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Amazon AI Introduces DataLore: A Machine Learning Framework that Explains Data Changes between an Initial Dataset and Its Augmented Version to Improve Traceability

Marktechpost

DATALORE uses Large Language Models (LLMs) to reduce semantic ambiguity and manual work as a data transformation synthesis tool. Second, for each provided base table T, the researchers use data discovery algorithms to find possible related candidate tables. These models have been trained on billions of lines of code.

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Data architecture strategy for data quality

IBM Journey to AI blog

Both approaches were typically monolithic and centralized architectures organized around mechanical functions of data ingestion, processing, cleansing, aggregation, and serving. As previously mentioned, a data fabric is one such architecture.

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Attivio Accelerates Business Intelligence and Big Data Projects with New Data Source Discovery Software

Attivio

June 8, 2015: Attivio ( www.attivio.com ), the Data Dexterity Company, today announced Attivio 5, the next generation of its software platform. And anecdotal evidence supports a similar 80% effort within data integration just to identify and profile data sources.” [1] Newton, Mass.,

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3 Takeaways from Gartner’s 2018 Data and Analytics Summit

DataRobot Blog

In Rita Sallam’s July 27 research, Augmented Analytics , she writes that “the rise of self-service visual-bases data discovery stimulated the first wave of transition from centrally provisioned traditional BI to decentralized data discovery.” We agree with that. Sallam | Cindi Howson | Carlie J.